Fuzzy logic algorithm for quantitative tissue characterization of diffuse liver diseases from ultrasound images

International Journal of Medical Informatics

Volumn 55, Issue 2, 1999, Pages 135-147

  Badawi, Ahmed M ^a   Derbala, Ahmed S ^a   Youssef, Abou Bakr M ^a  

^a CAIRO UNIVERSITY   (Egypt)

Author keywords

Diffuse disease; Fuzzy logic; Liver; Tissue characterization; Ultrasound parameters

Indexed keywords

ALGORITHMS; DATA ACQUISITION; FEATURE EXTRACTION; FUZZY SETS; MEDICAL IMAGING; MEMBERSHIP FUNCTIONS; SPECKLE; TISSUE; ULTRASONIC IMAGING;

DIFFUSE LIVER DISEASES;

MEDICAL COMPUTING;

ALGORITHM; ARTICLE; CLASSIFICATION; COMPUTER ASSISTED DIAGNOSIS; ENTROPY; FATTY LIVER; HUMAN; IMAGE ANALYSIS; LIVER CIRRHOSIS; LIVER DISEASE; MODEL; PATHOLOGY; PRIORITY JOURNAL; TISSUE CHARACTERIZATION; ULTRASOUND;

ALGORITHMS; FUZZY LOGIC; HUMANS; LIVER DISEASES; ULTRASONOGRAPHY;

EID: 0032828742     PISSN: 13865056     EISSN: None     Source Type: Journal    
DOI: 10.1016/S1386-5056(99)00010-6     Document Type: Article

References (29)

1. Kossof G. Display techniques in ultrasound pulse echo investigations. JCU. 2:1974;61.
2. Parker K.J., Lerner R.M., Waag R.C. Comparison of techniques for in vivo attenuation measurements. IEEE Trans. BME. 12(December):1988;35.
3. Oosterveld B.J., Thijssen J.M. Texture in tissue echograms speckle or information? J. Ultrasound Med. 9:1990;215.
4. Ophir J., Cespedes I., Ponnekanti H., Yazdi Y., Li X. Elastography: a quantitative method for imaging the elasticity of biological tissues. J. Ultrasound Imag. 13:1991;111.
5. Sclaps D., Rath R., Yolk J.F., Zuna I., Lorentz A., Lehmann K.J., Lorentz D., Kaick G.V., Lorentz W.J. Ultrasonic tissue characterization using a diagnostic expert system. Bacharach S.L. Information Processing in Medical Imaging. 1886;343 Martinus Nijhoff, Dordecht.
6. Raeth U., Schlaps D., Limberg B., Zuna I., Lorenz A., Van Kaik G., Lorenz W.J., Komoerell B. Diagnostic accuracy of computerized B-scan texture analysis and conventional ultrasonography in diffused parenchymal and malignant liver disease. J. Clin. Ultrasound. 13(2):1988;87.
7. Wu C.-M., Chen Y.-C., Hsieh K.-S. Texture features for classification of ultrasonic liver images. IEEE Trans. Med. Imag. 11(June):1992;2.
8. Kuc R.C. Clinical application of an ultrasound attenuation coefficient estimation technique for liver pathology. IEEE Trans. Biomed. Eng. 6(6):1980;27.
9. Waag R.C. A review of tissue characterization from ultrasonic scattering. IEEE Trans. BME. 12(12):1984;31.
10. A.M. Youssef, Y.M. Kadah, Ultrasonic Tissue Characterization of Breast Masses Using a Diagnostic Expert System, Proceedings of CAR-89, Berlin, Germany, June, 1989.
11. A.M. Youssef, A.A. Sharawi, K-sodata clustering analysis for diffuse liver disease, IEEE Proceeding Symposium on Ultrasound in Philadelphia, PA, 1990.
12. Insana M.F., Wagner R.F., Garra B.S. et al. Analysis of ultrasound image texture via generalized Rician statistics. J. Opt. Eng. 556(August):1986;153.
13. Nicholas D. Evaluation of backscattering coefficients for excised human tissues, results, interpretation and associated measurement. Ultrasound Med. Biol. 8:1982;17.
14. A.M. Youssef, D. Sclaps, W.J. Lorentz, Ultrasound textural synthesis using 2-D autoregressive models for pathology characterization, Proceedings of SPIE, 1987.
15. A.M. Badawi, A.M. Youssef, Effect of Static Compression on the Acoustical and Textural Parameters of the Liver with Correlation to Diffuse Diseases, Annual Meeting of Energy Society of Gastro. and Energy Society of Ultrasonoography, December, 1992.
16. A.M. Badawi, A.M. Youssef, Tissue Characterization of Diffuse Liver Diseases Using Neural Nets, Annual Meeting of Energy Society of Gastro. and Energy Society of Ultrasonography, December, 1992.
17. Y.M. Kadah, A.A. Farag, A.M. Youssef, A.M. Badawi Statistical and Neural Classifiers for Ultrasound Tissue Characterization, Artificial neural networks in engineering (ANNIE), St. Louis, MO, November, 1993.
18. Y.M. Kadah, A.A. Farag, A.M. Youssef, A.M. Badawi, Automatic Tissue Characterization from Ultrasound Imagery, SPIE, Boston, MA, September, 1993.
19. Kadah Y.M., Farag A.A., Zurada J.M., Badawi A.M., Youssef A.M. Quantitative algorithms for tissue characterization of liver diseases from ultrasound images. IEEE Med. Imag. J. August:1996;3.
20. A.M. Badawi, The Use of Sonoelasticity Imaging in Recognition of Diffuse Liver Diseases, M.Sc. Thesis of Engineering, Cairo University, Department of Biomedical Engineering, 1993.
21. L.A. Zadeh, Outline of a new approach to the analysis of complex systems and decision process, IEEE Trans. Syst. Man Cybern. 3 (1973).
22. C.C. Lee, Fuzzy logic in control systems, (Parts I, II) IEEE Trans. Syst. Man Cybern. 20 (March/April) (1990) 404.
23. G.J. Klir, T.A. Ffolger, Fuzzy Sets: Uncertainty, and Information, Prentice-Hall, Englewood Ckiffs, NJ (1992) 246.
24. Cheng Y.-Y., Mcinnis M., Mcinnis B. An algorithm for multiple attribute, multiple alternative decision problem based on fuzzy sets with application to medical diagnosis. IEEE Trans. Syst. Man Cybern. October:1980;20.
25. I.C. Bezdek, W.A. Fordon, Analysis of hypertensive patients by the use of fuzzy isodata algorithm, in: Proceedings of JACC, 1978, 3.
26. Torasso P. Fuzzy characterization of coronary diseases. Fuzzy Sets Syst. 5:1981;267.
27. Smets P. Medical diagnosis, fuzzy sets and degree of belief. Fuzzy Sets Syst. 5:1981;259.
28. Feng J., Lin W.-C., Chen C.-T. Epicardial boundary detection using fuzzy reasoning. IEEE Trans. Med. Imag. 2(June):1991;10.
29. Wang L.-X., Mendel J.M. Generating fuzzy rules by learning from examples. IEEE Trans. Syst. Man Cybern. 22:1992;1414.